{"categories":[{"label":"Application Frameworks","url":"https://skillfed.io/packages/category/software-development-libraries-application-frameworks/5"}],"enrichment":{"capability":"ipydatawidgets provides Jupyter widgets for efficiently sharing large numpy arrays across multiple widgets and packages using a single network sync, with built-in support for shape and dtype constraints.","skillfed_tags":["jupyter-extension","abandoned"],"use_cases":["Build Jupyter extensions that share large image or numerical arrays across multiple interactive widgets without re-transmitting data.","Constrain array shape and dtype in Jupyter widgets using built-in validators and trait types.","Reduce network overhead in Jupyter notebooks by syncing large array data once and reusing references across widgets.","Develop scientific visualization tools in Jupyter that need to pass array data between multiple coordinated widgets."],"what_it_does":"ipydatawidgets is a Jupyter extension that provides widgets for sharing large numpy arrays efficiently across multiple widgets and packages. Its core feature is the NDArrayWidget class, which wraps a numpy array and syncs it across the network only once, even when the same data is used by many different widgets. This avoids redundant data transmission and allows widgets to reference shared data via a single object.\n\nThe package is primarily useful for developers building Jupyter extensions that need to handle array data. It exposes trait types and serializers for numpy arrays, plus a DataUnion trait that lets other widgets accept either raw arrays or references to NDArrayWidget instances. The package is abandoned (last release June 2023) and has not been updated to work with recent Jupyter versions, so compatibility with current environments is uncertain.","worth_installing":"No, unless you are maintaining legacy Jupyter code that already depends on this package. The package is abandoned (no commits since June 2023, no releases since then), and manual Jupyter extension registration is error-prone. Modern Jupyter development should use actively maintained alternatives. If you must use it, test thoroughly with your Jupyter version first."},"id":"ipydatawidgets","links":{"html":"https://skillfed.io/packages/ipydatawidgets","md":"https://skillfed.io/packages/ipydatawidgets.md","pypi":"https://pypi.org/project/ipydatawidgets/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2023-06-14","license_spdx":null,"license_treatment":"permissive","name":"ipydatawidgets","python_support":"supports_current","summary":"A set of widgets to help facilitate reuse of large datasets across widgets"},"popularity":{"monthly_downloads":131114,"position":11604,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"4.3.5"}